Clinical and Experimental Dental Research
Machine Learning Prediction of Anterior Open‐Bite Development After Stabilization Splint Treatment in Temporomandibular Disorder
ABSTRACT Objectives To develop interpretable machine learning (ML) models for risk stratification of clinically meaningful anterior overbite decrease after stabilization splint therapy in temporomandibular disorder (TMD) patients, and to compare ML performance with conventional logistic regression. Materials and Methods This retrospective cohort included 87 TMD patients treated with stabilization splints, physical therapy, and pharmacologic therapy. Thirty‐five pre‐treatment cephalometric and demographic features w …